Batch Process Simulation Research Articles

PharmaPy: An object-oriented tool for the development of hybrid pharmaceutical flowsheets

Process design and optimization continue to provide computational challenges as the chemical engineering and process optimization communities seek to address more complex and larger scale applications. Software tools for digital design and flowsheet simulation are readily available for traditional chemical processing applications such as in commodity chemicals and hydrocarbon processing; however, tools for pharmaceutical manufacturing are much less well developed. This paper introduces, PharmaPy, a Python-based modelling platform for pharmaceutical manufacturing systems design and optimization. The versatility of the platform is demonstrated in simulation and optimization of both continuous and batch processes. The structure and features of a Python-based modeling platform, PharmaPy are presented. Illustrative examples are shown to highlight key features of the platform and framework.

A Combined Evaporation and Microalgal Cultivation Approach for Efficient Treatment of Landfill Leachate: Batch and Continuous Experiments and Process Simulation

Leachate from landfill is one of the most relevant unsolved environmental issues, in particular related to the high ammonia content. In this work, the possibility of treating this waste stream with a combined approach that includes both physical and biological treatment was assessed. The process is composed by a first evaporation/condensation step in an innovative industrial technology (WastWa) developed by Solwa SrL, that allows separating an aqueous stream in which about half of the water volume and most of the ammonia are recovered, and a concentrated leachate stream. The ammonia-rich water stream can be then sent to a microalgal cultivation step for N removal, while the concentrated waste can either be partially used to provide micronutrients for microalgal growth or delivered to phytodepuration. The feasibility of the process was tested at lab scale by carrying out both batch and continuous experiments with Acutodesmus obliquus, a microalgal species isolated from a pond containing pretreated leachate from an urban landfill located in Lazio (Italy). This strain was cultivated both in untreated leachate and in the aqueous outlet stream of the WastWa unit. A simulation model of the microalgal growth process was implemented in Aspen Plus, keeping into account the chemical equilibrium and ionic speciation of the nutrients in solution as well as the pH. The model was able to reproduce well the experimental data, and can therefore be a useful tool to evaluate the feasibility of the proposed process at large-scale.

Simulation and scale-up study for a chitosan–TiO2 nanotubes scaffold production

The use of TiO2 nanotubes as implant coating has gained good attention in the past decade. Their potential as regenerative materials for promoting new bone formation has recently been reported. In this paper, a novel chitosan–TiO2 nanotubes (CTNTs) scaffold production pathway was analyzed for its potential for commercial production. The production pathway was simulated using a commercial batch process simulation software, based on previously reported laboratory experimental results. An optimum production scale was then determined from the simulation study and subjected to sensitivity analysis. The sensitivity analysis was carried out to identify seven parameters that would affect the profitability of the process. The cost of TiO2 and autoclave reaction time were identified as the most dominant technical parameters which affected the main product cost and annual number of batches respectively.

Consequence Identification for Maloperation in Batch Process

Batch processes are important in chemical industry, in which operators usually play a major role and hazards may arise by their inadvertent acts. In this paper, based on hazard and operability study and concept of qualitative simulation, an automatic method for adverse consequence identification for potential maloperation is proposed. The qualitative model for production process is expressed by a novel directed graph. Possible operation deviations from normal operating procedure are identified systematically by using a group of guidewords. The proposed algorithm is used for qualitative simulation of batch processes to identify the effects of maloperations. The method is illustrated with a simple batch process and a batch reaction process. The results show that batch processes can be simulated qualitatively and hazards can be identified for operating procedures including maloperations. After analysis for possible plant maloperations, some measures can be taken to avoid maloperations or reduce losses resulted from maloperations.

Design of Simulation System for Batch Process

Process monitoring and fault diagnosis of batch process is a research focus in the industrial control field. In this paper, penicillin fermentation is taken as the research background, a visual batch process simulation system is designed based on mathematical models of an actual production process. By introducing different fault signals to the penicillin fermentation simulation process, the designed system can be used to simulate the real penicillin fermentation production process clearly. In the end, an ideal experimental simulation data for batch process fault diagnosis is provided.

Dynamic hybrid simulation of batch processes driven by a scheduling module

Simulation is now a CAPE tool widely used by practicing engineers for process design and control. In particular, it allows various offline analyses to improve system performance such as productivity, energy efficiency, waste reduction, etc. In this framework, we have developed the dynamic hybrid simulation environment PrODHyS whose particularity is to provide general and reusable object-oriented components dedicated to the modeling of devices and operations found in chemical processes. Unlike continuous processes, the dynamic simulation of batch processes requires the execution of control recipes to achieve a set of production orders. For these reasons, PrODHyS is coupled to a scheduling module ( ProSched) based on a MILP mathematical model in order to initialize various operational parameters and to ensure a proper completion of the simulation. This paper focuses on the procedure used to generate the simulation model corresponding to the realization of a scenario described through a particular scheduling.

Analysis of a reactive extraction process for biodiesel production using a lipase immobilized on magnetic nanostructures

Magnetic nanoparticles were prepared by coprecipitating Fe(2+) and Fe(3+) ions in a sodium hydroxide solution and used as support for lipase. The lipase-coated particles were applied in a reactive extraction process that allowed separation of the products formed during transesterification. Kinetics data for triolein and ethanol consumption during biodiesel (ethyl oleate) synthesis together with a thermodynamic phase equilibrium model (liquid-liquid) were used for simulation of batch and continuous processes. The analysis demonstrated the possibility of applying this biocatalytic system in the reactive zone using external magnetic fields. This approach implies new advantages in efficient location and use of lipases in column reactors for producing biodiesel.

Batch process monitoring in the original measurement's space

Quality control and safety related issues have become more and more important in industrial production of high added value products and chemical specialities during last years. In this regard, many successful applications of multivariate statistical process control ( MSPC) for monitoring and diagnosis of batch processes have been presented. It is a common industrial practice to monitor the batch progress by exploiting the information contained in a historical database of successful batches using projection techniques such as principal components analysis ( PCA), partial least squares ( PLS) and independent component analysis ( ICA). In this work, a new MSPC strategy for batch process monitoring is presented. Its distinctive feature is that it works in the space of the original variables. The technique uses only the T 2-statistic for detection and identification purposes. The identification of the set of observations that signal the fault is accomplished by decomposing the T 2-statistic as a unique sum of each variable contribution. Performance comparisons among the proposed strategy and the most popular PCA-based approaches are carried out by simulation of polymerization and penicillin cultivation batch processes. Results show that the new approach can be successfully applied to monitor this kind of processes since it works very well during both fault detection and identification stages.

Evaluation of Nitrification Kinetics and Biological Phosphorus Removal using Batch Rate Testing, Profile Sampling, and Process Simulation Modeling

Evaluation of Nitrification Kinetics and Biological Phosphorus Removal using Batch Rate Testing, Profile Sampling, and Process Simulation Modeling

An integrated approach for water minimisation in a PVC manufacturing process

This paper presents a water minimisation study carried out for a polyvinyl chloride (PVC) resins manufacturing plant. Due to the complexity of the mixed batch and continuous polymerisation process, an integrated process integration approach, which consists of process synthesis, analysis and optimisation was used for this work. A simulation model was first developed in a batch process simulation software, SuperPro Designer V6.0, based on the operating condition of a PVC manufacturing process. The batch simulation model captured the essential information needed for a water minimisation study, e.g. process duration, water mass flow, etc. Data extracted from the simulation model was later used in the water minimisation study, utilising the widely established process synthesis technique of water pinch analysis. Two water saving scenarios were presented. Scenario 1 reports a fresh water and wastewater reduction of 28.5 and 90.1% respectively, for the maximum water recovery scheme without water storage system. In Scenario 2, higher fresh water and wastewater reduction are reported at 31.7 and 100% respectively, when water storage tank is installed in the water network.

Streamlined life cycle assessment of residue utilization options in Tongkat Ali (Eurycoma longifolia) water extract manufacturing process

Life cycle assessment (LCA) is often used to compare alternative process options in terms of their overall impact on the environment to easily identify the most environmentally friendly alternative. In this work, a streamlined LCA study was conducted to assess three different residue utilization schemes for Tongkat Ali (Eurycoma longifolia) extract production. The case study was firstly simulated using a batch process simulation software. The results of mass and energy balances obtained from the simulation software were then subjected to life cycle analysis. By evaluating the different schemes for using the fibrous residue from the extraction process, the potential for environmental process improvement was identified. Overall, use of the residue as process fuel was found to be the most environmentally friendly option. It produces the least emissions and reduces resource usage per unit of product than the other options evaluated.

Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm

Chemical batch processes are typically used for the production of speciality chemicals and pharmaceuticals. Due to the still growing importance of this type of processing, design methods are required that take into account the special requirements and constraints in the corresponding production facilities. We developed a method that optimizes the design of a single chemical process to be implemented in an existing multi-purpose batch plant, in which a well-defined set of equipment units is available for realizing this process. In the optimization, three objectives with different priorities are considered. A flexible metaheuristic algorithm, Tabu Search (TS), has been implemented to solve this multi-objective combinatorial non-linear problem. We started from a basic form of TS to determine the effectiveness of this version as well as establish the relative strengths and weaknesses of first level TS strategies. Our investigation includes a thorough examination of algorithm parameters and of implementation issues to identify algorithm settings that can handle the whole class of problems considered. Overall, we concluded that the basic form of TS—using fixed default settings—exhibits highly attractive performance features for solving the problems at hand. Moreover, comparison with a multi-start steepest descent algorithm shows that a basic TS approach conducts a global search more effectively. As illustrated by three case studies, the new method is well suited for identifying optimal designs of a chemical process to be implemented in an existing multi-purpose batch plant. The approach is particularly suited for considering multiple prioritized objectives and for enabling the use of external (e.g. commercial) batch process simulation software as a black-box model for the process evaluations.

Dynamic modeling and simulation of a three-phase fluidized bed batch process for wastewater treatment

Batch operation with different starting substrate concentrations (biological oxygen demand (BOD 5)) and biomass concentrations (mixed liquor volatile solid (MLVS)) were performed on a completely mixed three-phase fluidized bed reactor used in treating simulated domestic waste water. The mixed culture microorganisms used were contained in a biofilm attaching to cement balls. The data obtained were fitted to five different kinetic rate equations. The kinetic parameters of each model were obtained using a Gauss–Newton nonlinear regression analysis method. It was found that the Haldane model incorporating endogenous metabolic consumption (Endo–Haldanc model), best described the kinetics of the biological reaction inside the three-phase fluidized bed reactor. This is due to the fact that this model can both account for the effects of cell death and/or endogenous metabolism at low concentration and of substrate inhibition at high concentration.

Efficient Simulation Modeling of an Integrated High-Level-Waste Processing Complex

An integrated computational tool named the Production Planning Model (ProdMod) has been developed to simulate the operation of the entire high-level-waste complex (HLW) at the Savannah River Site (SRS) over its full life cycle. ProdMod is used to guide SRS management in operating the waste complex in an economically efficient and environmentally sound manner. SRS HLW operations are modeled using coupled algebraic equations. The dynamic nature of plant processes is modeled in the form of a linear construct in which the time dependence is implicit. Batch processes are modeled in discrete event-space, while continuous processes are modeled in time-space. The ProdMod methodology maps between event-space and time-space such that the inherent mathematical discontinuities in batch process simulation are avoided without sacrificing any of the necessary detail in the batch recipe steps. Modeling the processes separately in event- and time-space using linear constructs, and then coupling the two spaces, has accelerated the speed of simulation compared to a typical dynamic simulation. The ProdMod simulator models have been validated against operating data and other computer codes. Case studies have demonstrated the usefulness of the ProdMod simulator in developing strategies that demonstrate significant cost savings in operating the SRS HLW complex and in verifying the feasibility of newly proposed processes.

Modular representation of complex hybrid systems: application to the simulation of batch processes

A modelling approach of complex systems is presented. The goal is to define a modular and non-causal representation able to describe hybrid dynamics, and to generate automatically the models corresponding to the different configurations of the real system. These models can then be used to simulate process evolution. In this paper, we define the structure of the basic model blocks and the interactions of these blocks through different kinds of signals.

A new index 2 Runge-Kutta method for the simulation of batch and discontinuous processes

A solver capable of handling discontinuous differential-algebraic equations, up to a different index of 2, has been implemented in the process simulator NIMBUS. This solver is constructed from a Runge-Kutta method and so, unlike other high index solvers, does not require symbolic differentiation of the equation set. This paper outlines the solver, its implementation, and compares its performance with that of other solvers.

A combined batch process simulation in a production support environment

Productive and safety production of high quality products is required in batch processes, and the importance of generating control recipes, which defines operations of each batch, is increasing. The control recipe is generated through the evolutionary cycle: initiate operations, evaluate performance and modify operations, and combined batch process simulator plays an important role for evaluating the performance. This paper describes the development of production support environment to generate control recipe, and embedding combined discrete/continuous batch process simulator. Based on the activity model of batch production, a framework of the support environment is proposed, and to date development of embedding combined batch process simulator is explained.

Handling the increasing complexity of detailed batch process simulation and optimisation

Production-economics, once dominated by efficiency factors or cost-effectiveness ratios, have been incorporating inventory reduction, flexibility and quality improvement as additional factors. But production also has to take account of environmental control. If a linkage of these production concepts with the methodical approaches of an optimised production will be successful, high efficiency reserves can be activated. In this work a prospective and perspective view is given on the systematic methodologies currently developed and the software available that addresses the dominant current trends in the modeling, simulation and optimization of batch process industries, which represent the fastest growing segment of the process industries.

An open software architecture for batch process simulation

Simulation of recipe driven batch processes is a complex demanding task. It can be performed either with general purpose simulators, causing a high modelling effort, or with specific tools which often lack flexibility. Neither of these approaches is appropriate in all cases. In this contribution, we outline a software architecture for batch process simulation which is flexible enough to be adapted to meet the particular requirements of the simulation problem at hand. It consists mainly of the elements model creation, output clients, simulator, and user interface. All these components are exchangeable to offer the software solution which is best suited for the specific problem. The software concepts are presented in terms of design patterns.

BaSiP — Batch process simulation with dynamically reconfigured process dynamics

Recipe-driven automatic production is widely used to reduce the load on the operators and to allow them to focus on the high level tasks of assignment of equipment, sequencing, and scheduling. Simulation can support these functions by answering if .. then questions, finding bottlenecks or underused equipment, testing of recipes, detecting illegal or dangerous operations. The major challenge of the simulation of batch plants is the hybrid nature of the system, combined with frequent changes of the structure of the system, which in our opinion necessitates a dynamic configuration of the simulation model during the simulation run. This is realized in the program BaSiP which is designed to simulate the operation of recipe-driven multipurpose batch plants.